Controlling active brownian particles in complex settings

We show active Brownian particles (passive Brownian particles in a bacterial bath) switches between two long-term behaviors, i.e. gathering and dispersal of individuals, in response to the statistical properties of the underlying optical potential. © 2017 OSA

Disorder-mediated crowd control in an active matter system

Living active matter systems such as bacterial colonies, schools of fish and human crowds, display a wealth of emerging collective and dynamic behaviours as a result of far-from-equilibrium interactions. The dynamics of these systems are better understood and controlled considering their interaction with the environment, which for realistic systems is often highly heterogeneous and disordered. Here, we demonstrate that the presence of spatial disorder can alter the long-term dynamics in a colloidal active matter system, making it switch between gathering and dispersal of individuals. At equilibrium, colloidal particles always gather at the bottom of any attractive potential; however, under non-equilibrium driving forces in a bacterial bath, the colloids disperse if disorder is added to the potential. The depth of the local roughness in the environment regulates the transition between gathering and dispersal of individuals in the active matter system, thus inspiring novel routes for controlling emerging behaviours far from equilibrium

Threshold effect on particle tracking algorithms

34th International Physics Congress on Turkish Physical Society, TPS 2018Automated particle tracking algorithms are widely used by soft matter physicists as a research tool to detect and construct the trajectories of micron-sized particles in ffuids. Analyzing these trajectories will uncover the physics of the investigated particles mainly on the type of motion they undergo making them suitable for potential applications. A plethora of methods has been proposed and used for detection and tracking. In this work, we examine the performance of two commonly used tracking algorithms in terms of threshold dependencies in digital video images. One of them is the centroid method (CM), a well-known and used algorithm and the other is radial symmetry method (RSM) which is recently proposed. Here, we generate the synthetic digital video images consisting of randomly placed multiple particles and compare the absolute errors on the particle detection by varying threshold values. Our results suggest that both algorithms show dependence on the threshold value and on comparison RSM algorithm performs better than the CM algorithm when the noise level is zero. Moreover, the measured absolute errors show a strong dependence on threshold values when noise levels are increased (up to 20) especially for the RSM algorithm. © 2018 Author(s)